Marine resources alter tundra food web dynamics by subsidizing a terrestrial predator on the sea ice
Bibliographic record
Abstract
Predator use of resource subsidies can strengthen top-down effects on prey when predators respond numerically to subsidies. Although allochthonous subsidies are generally transported along natural gradients, consumers can cross ecosystem boundaries to acquire subsidies, thereby linking disparate ecosystems. In coastal Arctic ecosystems, terrestrial predators can easily cross into the marine environment (sea ice) during winter, which is a foraging strategy that Arctic foxes (Vulpes lagopus) use to access marine subsidies – largely seal carrion leftover from polar bear (Ursus maritimus) kills – especially when rodent abundance is low. Terrestrial predator use of marine subsidies may strengthen the top-down control of tundra food webs, but this hypothesis had remained untested. We took an ecosystem-level approach towards evaluating tundra food web dynamics at the terrestrial–marine interface by assessing: (i) how winter environmental conditions affect rodent abundance and marine subsidy availability, (ii) the responses of the Arctic fox population to this winter food variability, and (iii) the subsequent effects of Arctic foxes on the reproductive success of other tundra prey (Canada geese [Branta canadensis interior]). Arctic foxes responded numerically to rodent abundance and marine subsidy availability, which were positively related to greater snow and sea ice persistence, respectively. Canada goose reproductive success, in turn, was negatively related to Arctic fox abundance. Long-term trends in Canada goose reproduction and snow persistence on the tundra also indicate an ongoing phenological mismatch between nesting initiation and the onset of spring. Our results reveal short-term apparent competition between rodents and geese through a shared predator, Arctic foxes, which contrasts with prior studies evaluating rodent–goose–predator relationships. Moreover, we establish a link between tundra and sea ice food webs by demonstrating seal availability has a negative indirect effect on goose reproduction via carrion provisioning from polar bears to Arctic foxes, both of which are undergoing long-term population declines evidently driven by climate-related changes in prey abundance and availability. Given the importance of the winter environment in mediating these trophic interactions, we contextualize our study within ongoing climate change and highlight the vulnerability of this likely widespread terrestrial–marine linkage in a warming Arctic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".